Replica Analytics is the premier science-based Synthetic Data Generation technology provider to the healthcare industry. Share, reuse, protect, amplify, and augment your sensitive data with our highly advanced privacy and utility preserving methodologies.
Our synthetic data generation technology offers trusted solutions to protect sensitive information and share data more freely with fewer regulatory constraints. It is a responsible way for organizations to share and reuse data internally and externally.
Backed by research, our technology is widely used in the healthcare and pharmaceutical industries, as well as other sectors.
Using real datasets, we employ machine learning and deep learning techniques to generate on-demand privacy-and-utility-preserving, synthetic datasets.
Our machine learning models retain the statistical properties and patterns of the original dataset to produce high-utility synthetic data with privacy-enhancing properties. We understand all datasets are not made equal and have built our technology to work with both tabular and relational, large and small datasets.
With no one-to-one mapping between the original and synthetic data, data generated by Replica Synthesis is considered non-identifiable. This can be tested using our unified privacy assessments.
With decades of experience in privacy protection, we have one of the most advanced privacy assurance technologies in the industry, giving you the compliance evidence needed to demonstrate very small privacy risks in your synthetic data.
Our privacy assurance solutions implement a complete risk assessment methodology. The only one on the market covering multiple disclosure risks simultaneously.
Unified solutions for evaluating privacy and utility are unique to Replica Analytics. Our technology is an advanced form of de-identification and offers easier, quicker access to data and fewer constraints than traditional methods.
Synthetic clinical trial data generated by Replica Analytics is being used
across multiple business lines, such as data science and statistical
programming. This has allowed easy and broader access to data for our
internal teams and partners, and enables us to accelerate our innovation
Realistic synthetic data from Replica Analytics allowed us to demonstrate our data integration and analytics software to a prospective client quickly. What was going to be a months-long process to deal with the data privacy concerns and regulations happened in only days. Synthetic data helped us prove out the business case and accelerate the customer acquisition significantly.
Our team brings deep academic expertise and decades of international knowledge in machine learning, privacy protection and data analysis. We are credible experts with experience in applied research and building successful businesses that serve large global clients.
SVP and General Manager
Director Of Data Science